- Description:
10 large 5000 x 5000 textured colorectal cancer histology images
Source code:
tfds.image_classification.ColorectalHistologyLarge
Versions:
2.0.0
(default): New split API (https://tensorflow.org/datasets/splits)
Download size:
707.65 MiB
Dataset size:
464.91 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'test' |
10 |
- Feature structure:
FeaturesDict({
'filename': Text(shape=(), dtype=string),
'image': Image(shape=(5000, 5000, 3), dtype=uint8),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
filename | Text | string | ||
image | Image | (5000, 5000, 3) | uint8 |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{kather2016multi,
title={Multi-class texture analysis in colorectal cancer histology},
author={Kather, Jakob Nikolas and Weis, Cleo-Aron and Bianconi, Francesco and Melchers, Susanne M and Schad, Lothar R and Gaiser, Timo and Marx, Alexander and Z{"o}llner, Frank Gerrit},
journal={Scientific reports},
volume={6},
pages={27988},
year={2016},
publisher={Nature Publishing Group}
}